Industry · Banks, insurers, asset managers, fintechs
AI agents for financial services that survive the audit.
Banks, insurers, asset managers, fintechs, leasing and payment companies run on documents, rules and supervision. We build AI agents that take over the reading, sorting and drafting inside those processes, keep every decision with a person, and leave an audit trail your compliance function can work with.
Where AI pays off in financial services
The opportunity is not in replacing decisions. It is in the hours your people spend preparing them.
A claims handler, an onboarding specialist or a compliance officer spends most of the day collecting documents, extracting facts, checking them against rules and writing the result down. The judgement at the end takes minutes. Everything before it takes hours, and it is precisely the kind of work language models now do reliably when they are given the right sources and clear boundaries.
So that is where we start: agents that read incoming documents, check completeness and consistency, draft the file note or the customer reply, and hand a prepared case to the person who decides. Decision, release and any commitment to the customer stay human. That keeps you within supervisory expectations and the EU AI Act, and it makes the business case simple to measure.
We work with retail and corporate banks, insurers, asset managers, fintechs, leasing and payment providers in Germany, Austria, Switzerland and wider Europe, in English and German. Everything we build is designed around the questions your second line of defence will ask.
- Typical starting pointsClaims, onboarding, service, complaints, compliance support
- Operating principleAgents prepare, people decide
- Built forGDPR, EU AI Act, outsourcing rules, audit trails
- First stepReadiness assessment, or a 6–8 week pilot
Use cases in banking, insurance and fintech
Eight workflows where agents already carry real load in financial institutions, each with the human checkpoint that belongs in it.
Claims intake and document processing
An agent receives the claim by email, portal or scanned post, extracts the facts, checks the cover, requests missing documents and drafts the settlement proposal. The claims handler reviews and decides. Simple, complete claims move in hours instead of days.
KYC and onboarding checks
Identity documents, register extracts, ownership structures and screening hits are collected and compared, and the discrepancies are listed. The onboarding officer sees a prepared file with sources, not a verdict. Approval and rejection remain a human decision.
Customer service agents
Agents answer questions on balances, cover, contracts and procedures within a defined scope, connected to your core systems, and escalate everything else. Written channels first, voice where it fits. See AI agents for customer service.
Advisor knowledge assistants
An assistant over your product documentation, terms, internal guidelines and regulatory circulars, with every answer citing its source. Advisors and back-office staff find the right passage in seconds instead of asking the one colleague who knows. Built as a knowledge assistant.
Complaint handling and categorisation
Incoming complaints are classified by product, cause and severity, mapped to the reporting categories you use, and routed with a draft response. The complaints team keeps ownership of the reply and of the root-cause record.
Compliance monitoring and reporting drafts
Agents screen transactions, communications or process logs against your rules, flag exceptions with their reasoning, and pre-write the sections of recurring reports that are pure aggregation. Internal audit and compliance spend their time on findings, not on collection.
Contract and policy document review
Loan agreements, policy wordings, supplier and outsourcing contracts are checked against your playbooks: missing clauses, deviations, deadlines and obligations, listed with references. Legal reviews faster and more consistently. See legal and compliance.
Anomaly flags for fraud analysts
Language models do not replace your fraud scoring. They help the analyst: summarising a flagged case, pulling related documents and communications together, and drafting the note for the investigation file. The analyst decides what happens next.
Constraints specific to financial services
Every design decision we make in this industry answers to one of these six. They shape the architecture before anyone chooses a model.
Supervisory expectations
BaFin, the EBA guidelines, MaRisk and VAIT for banks and the corresponding frameworks for insurers set expectations for IT risk, process control and documentation. DORA adds ICT risk management and third-party oversight. We design agents so that scope, controls and monitoring can be documented in the language supervisors expect. Which rules apply in detail is a question for your compliance and legal teams; we build so that their answer comes easily.
Outsourcing rules for cloud and AI vendors
Using a model provider or an agent platform may count as outsourcing or as an ICT third-party service, which affects contracts, exit strategies, risk assessments and notification duties. We support the assessment with an architecture that can switch providers and with the documentation your outsourcing officer needs.
Model risk and explainability
Generative models are not deterministic. That is manageable when the agent's role is preparation and its reasoning, sources and drafts are visible to the person deciding. We add evaluation suites, versioning and logging so you can show how the system behaves, not just that it worked in a demo.
EU AI Act high-risk categories
Creditworthiness assessment of natural persons and risk assessment or pricing in life and health insurance are listed as high-risk under the EU AI Act. We do not build automated decisions there. We build support for the people who decide, and we document the classification. Confirm the current legal status with counsel; guidance and timelines are still evolving.
Data residency and confidentiality
Customer data, banking secrecy and internal documents have to stay where your data-protection officer can defend them. We work with EU-hosted model endpoints, private cloud or open-weight models on your own infrastructure where required. Read our note on sovereign AI and EU hosting.
Audit trails by default
Every agent action, source, draft and human decision is logged so that internal audit can follow it years later. This is not an add-on; it is part of the first sprint.
How we start in a supervised institution
Scoping with the second line in the room
Compliance, data protection, information security and, where relevant, the outsourcing officer join the first workshop. We pick one bounded process, define what the agent may and may not do, and agree the metrics.
Risk classification and architecture
A preliminary EU AI Act and GDPR assessment for the use case, the data flows, the hosting decision and the human checkpoints, written down so that approvals do not stall the build.
Pilot with real cases
We build the agent on your documents and systems, run it in shadow mode next to the existing process, measure it against the baseline and iterate with the team.
Production, monitoring and scale-out
Go-live with logging, evaluation and an escalation path, then the next process on the list. Managed AI operations keeps the system reliable and documented.
Frequently asked questions
Can a supervised institution use AI agents at all?
Yes, within the frameworks that already govern your IT and your outsourcing. The key is scope: agents that prepare, draft and check, with people deciding inside a documented control environment, fit existing governance far more easily than autonomous decision systems. We design for that from the first workshop and involve your second line early, so the question gets answered with documentation rather than debate.
Does the EU AI Act make our use cases high-risk?
Only some. Credit scoring of natural persons and risk assessment or pricing in life and health insurance are named as high-risk. Claims intake, document checks, knowledge assistants, complaint routing or drafting support generally are not, although GDPR and your sector rules still apply. We give each use case a preliminary classification and recommend confirming it with your legal team, since guidance and timelines are still developing. Our EU AI Act guide explains the categories.
Where does our data go?
That is your choice, and we make sure it is a real one. Options range from EU-hosted endpoints of the large model providers to models running in your private cloud or on your own hardware. We match the option to the sensitivity of the data and the outsourcing rules you operate under, and we document the data flows for your data-protection officer.
How do you make agent output explainable to auditors?
By not letting agents take the decisions that would need explaining, and by logging everything else. Each output carries its sources, the intermediate steps and the version of the prompts and models used. Human decisions are recorded together with the prepared material they were based on. An auditor can replay a case from end to end.
Which process should a bank or insurer start with?
One with high volume, clear documents and a measurable cycle time: claims intake, onboarding document checks, complaint categorisation or an internal knowledge assistant for advisors. They pay off quickly, they rarely touch high-risk categories, and they teach your organisation how to run agents before you tackle anything harder. A readiness assessment settles the choice in two to three weeks.
Related
AI governance, EU AI Act & GDPR
An AI register, risk classification under the EU AI Act, GDPR-aligned processes and a usage policy your teams will actually follow, built together with your lawyers and your data protection officer.
AI agents for customer service
Ticket triage, agent assist with sources, automated resolution for defined categories and a clean hand-over to people when confidence drops.
AI agents for legal & compliance
First-pass contract review, obligation tracking, regulatory monitoring and policy Q&A, with a lawyer approving everything that leaves the department.
The EU AI Act for companies
Who the regulation applies to, which risk tier your use cases fall into, what has applied since 2025, and a seven-step plan to get compliant without drama.
Let's find the first workflow worth automating.
A 30-minute intro call, no slides and no obligation. We listen, ask about your processes, and tell you honestly where AI agents would pay off and where they would not.